This paper deals with multi-arms fruits picking in orchards. More specifically, the goal is to control the arms to approach the fruits position. To achieve this task a VPC strategy has been designed to take into accou...
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ISBN:
(纸本)9789897583803
This paper deals with multi-arms fruits picking in orchards. More specifically, the goal is to control the arms to approach the fruits position. To achieve this task a VPC strategy has been designed to take into account the dynamic of the environment as well as the various constraints inherent to the mechanical system, visual servoing manipulation and shared workspace. Our solution has been evaluated in simulation using on PR2 arms model. Different models of visual features prediction have been tested and the entire VPC strategy has been run on various cases. The obtained results show the interest and the efficiency of this strategy to perform a fruit picking task.
作者:
Belda, KvetoslavCzech Acad Sci
Inst Informat Theory & Automat Dept Adapt Syst Pod Vodarenskou Vezi 4 Prague 18208 8 Czech Republic
The paper deals with path smoothing and time parametrization procedures intended for motion control of industrial machine tools and robots. Path smoothing, considered in this paper, is based on the application of Bezi...
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ISBN:
(纸本)9789897583803
The paper deals with path smoothing and time parametrization procedures intended for motion control of industrial machine tools and robots. Path smoothing, considered in this paper, is based on the application of Bezier curves. A possible straightforward solution ensuring compliance with given admissible positional tolerances is introduced. Consequent time parametrization considered here employs arc length and specific construction of acceleration polynomials. It describes the motion along the obtained smoothed curve geometry. It is given by timing the arc length, thus the construction of the feed rate profile. The key parts of the time parametrization comprise: computation of path length;time parametrization with respect to arc length;and decomposition to the individual Cartesian components describing individual curve coordinates. The theoretical results are presented by representative examples in 2D and 3D spaces.
This paper presents the development of an integrated strawberry harvesting robotic system tested in lab conditions in order to contribute to the automation of strawberry harvesting. The developed system consists of th...
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ISBN:
(纸本)9789897583803
This paper presents the development of an integrated strawberry harvesting robotic system tested in lab conditions in order to contribute to the automation of strawberry harvesting. The developed system consists of three main subsystems;the vision system, the manipulator and the gripper. The procedure for the strawberry identification and localization based on vision is presented in detail. The performance of the robotic system is assessed by the results of experiments that take place in the lab and they are related to the recognition of occluded strawberries, the check of the strawberries for possible bruises after the grasping and the accuracy of detection of the strawberries' location. The results show that the developed vision algorithm recognizes correctly every single strawberry and has high accuracy in recognizing occluded strawberries in which the largest part of each of them is visible. A small localization error results in a correct grasp and cut without causing damage to the fruit.
In this work the application of six-axis robots for robot-based industrial X-ray computed tomography (CT) imaging is investigated. In contrast to classical Cartesian manipulators with a turntable used in industrial co...
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ISBN:
(纸本)9789897583803
In this work the application of six-axis robots for robot-based industrial X-ray computed tomography (CT) imaging is investigated. In contrast to classical Cartesian manipulators with a turntable used in industrial cone-beam CT, robots offer increased flexibility regarding scanning trajectories. The increased flexibility with respect to scanning trajectories helps to gather highly informative content from alternative ray paths for a high-quality 3D reconstruction of the object to be scanned. Using numerical simulations we show that this additional informations increase the image quality of a CT scan of a multi-material measuring object, consisting of tantalum spheres and a carbon structure.
Autonomous navigation in off-road environments is a challenging task for mobile robots. Recent success in artificial intelligence research demonstrates the suitability and relevance of neural networks and learning app...
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ISBN:
(纸本)9789897583803
Autonomous navigation in off-road environments is a challenging task for mobile robots. Recent success in artificial intelligence research demonstrates the suitability and relevance of neural networks and learning approaches for image classification and off-road robotics. Nonetheless, meaningful decision making processes require semantic knowledge to enable complex scene understanding on a higher abstraction level than pure image data. A promising approach to incooperate semantic knowledge are ontologies. Especially in the off-road domain, scene object correlations heavily influence the navigation outcome and misinterpretations may lead to the loss of the robot, environmental, or even personal damage. In the past, behavior-based control systems have proven to robustly handle such uncertain environments. This paper combines both approaches to achieve a situation-aware navigation in off-road environments. Hereby, the robot's navigation is improved using high-level off-road background knowledge in form of ontologies along with a reactive, and modular behavior network. The feasibility of the approach is demonstrated within different simulation scenarios.
In this research, we focus on the 6D pose estimation of known objects from the RGB image. In contrast to state of the art methods, which are based on the end-to-end neural network training, we proposed a hybrid approa...
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ISBN:
(纸本)9789897583803
In this research, we focus on the 6D pose estimation of known objects from the RGB image. In contrast to state of the art methods, which are based on the end-to-end neural network training, we proposed a hybrid approach. We use separate deep neural networks to: detect the object on the image, estimate the center of the object, and estimate the translation and "in-place" rotation of the object. Then, we use geometrical relations on the image and the camera model to recover the full 6D object pose. As a result, we avoid the direct estimation of the object orientation defined in SO3 using a neural network. We propose the 4D-NET neural network to estimate translation and "in-place" rotation of the object. Finally, we show results on the images generated from the Pascal VOC and ShapeNet datasets.
This paper investigates the progression of human hand trajectory variabilities during a pick-and-place task. A user study is conducted and human hand positions are tracked optically. Standard deviations of human hand ...
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ISBN:
(纸本)9789897583803
This paper investigates the progression of human hand trajectory variabilities during a pick-and-place task. A user study is conducted and human hand positions are tracked optically. Standard deviations of human hand positions over all trajectories within a trial are computed point-wise orthogonally to the direct path between start and goal positions. Statistical tests reveal a decrease of standard deviations from hand start to goal positions. Moreover, stronger variations of standard deviations are noted in during the center part of the trajectories. Contrary to expectations, a longitudinal study design does not reveal learning effects in terms of reduction of trajectory variabilities. The results suggest, that uncertainties of human hand positions increase with the distance to a goal location and could constitute a larger risk for collisions within a cooperative human-robot pick-and-place scenario, e.g. assembly.
Wheelchairs have improved the lives of many people with limited mobility. Yet, to this day, conventional wheelchairs are still not a viable option for mobility independence in cases of people with severe weakness or p...
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ISBN:
(纸本)9789897583803
Wheelchairs have improved the lives of many people with limited mobility. Yet, to this day, conventional wheelchairs are still not a viable option for mobility independence in cases of people with severe weakness or poor coordination e.g. Amyotrophic Lateral Sclerosis (ALS). Smart wheelchairs (SWs) overcome many of these limitations by adding an extra layer of intelligence to the system. SWs have so far remained mostly inaccessible to the general public, due to a limited market presence and steep costs. This paper thus presents the design and implementation of a novel SW which makes the upgrade of a commercially available motorised wheelchair to a SW a much simpler process. The system is a complete implementation offering low-level hardware control, a specialised ROS architecture and autonomous navigation algorithms allowing shared user control or fully-autonomous movement. Contrary to most other published works, the focus of this paper is to implement a fully-featured working prototype with minimal hardware complexity and an efficient modular software development environment. Initial practical tests in typical use scenarios showcased the successful operation of the complete system. The developed prototype SW has the potential to restore autonomy to people who are unable to use conventional or powered wheelchairs.
We propose a symbolic self-triggered controller synthesis procedure for non-deterministic continuous-time nonlinear systems without stability assumptions. The goal is to compute a controller that satisfies two objecti...
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ISBN:
(数字)9781728177090
ISBN:
(纸本)9781728177106
We propose a symbolic self-triggered controller synthesis procedure for non-deterministic continuous-time nonlinear systems without stability assumptions. The goal is to compute a controller that satisfies two objectives. The first objective is represented as a specification in a fragment of LTL, which we call 2-LTL. The second one is an energy objective, in the sense that control inputs are issued only when necessary, which saves energy. To this end, we first quantise the state and input spaces, and then translate the controller synthesis problem to the computation of a winning strategy in a mean-payoff parity game. We illustrate the feasibility of our method on the example of a navigating nonholonomic robot.
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